Built at LinkedIn, Pinot is an open source, distributed, and scalable OLAP data store that we use as our de-facto near-real-time analytics service. We’ve previously discussed how and why we built Pinot to power a wide spectrum of use cases, including internal business intelligence dashboards to analyze highly-dimensional data and “Who Viewed My Profile” to...
metrics Articles
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- Topics:
- Pinot,
- metrics,
- Data,
- Open Source
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Co-authors: Yen-Jung Chang, Yang Yang, Xiaohui Sun, and Tie Wang At LinkedIn, ThirdEye is the backbone of our monitoring toolkit. We use it to keep track of a variety of metrics, whether it be related to production infrastructure and AI model performance, or business impact, such as page view or click count. It’s a key quality assurance system because it...
- Topics:
- monitoring,
- Pinot,
- metrics,
- Data
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Earlier this year, we published a blog post sharing details on ThirdEye, LinkedIn’s comprehensive platform for real-time monitoring and root cause analysis. LinkedIn relies on ThirdEye to monitor a wide spectrum of metrics, ranging from product health to high-level business metrics, and also including machine learning model performance. While monitoring is a...
- Topics:
- monitoring,
- Pinot,
- metrics,
- Data
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Co-authors: Burcu Baran, Xiaojing Dong, Chi-Yi Kuan, Emily Huang, and Tiger Zhang At LinkedIn, we have more than 630M members, 30M...
- Topics:
- data science,
- machine learning,
- metrics,
- Data,
- events
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At LinkedIn, we have many different monitoring systems—each with its own role and granularity— ranging from quarterly reports about...
- Topics:
- Pinot,
- real time monitoring,
- metrics,
- Data
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Co-authors: Ken Soong, Liz Li, Yang Zhou, and Xin Fu Growth hacking is a common buzzword among startups and mature companies alike. At...
- Topics:
- data science,
- metrics,
- growth